论文标题
实时估计Covid-19使用电力市场数据对经济活动的短期影响的实时估计
Real-time estimation of the short-run impact of COVID-19 on economic activity using electricity market data
论文作者
论文摘要
迄今为止，Covid-19-19造成了超过800万例确认的病例和500,000例死亡。为了应对这种紧急情况，许多国家提出了一系列社会持续的措施，包括锁定和企业的临时关闭，以遏制感染的传播。因此，大流行一直在对社会的各个方面产生前所未有的破坏。本文表明，高频电力市场数据可用于估计Covid-19对经济的因果，短期影响。在当前不确定的经济条件下，及时性至关重要。与延迟几个月发布的官方统计数据不同，我们的方法几乎每天都可以监视遏制政策的影响，衰退的程度以及衡量引入的货币和财政刺激是否有效。我们说明了意大利日趋势电力市场的每日数据的方法论。毫不奇怪，我们发现遏制措施导致经济活动大大减少，并且2020年5月末的GDP仍然比没有爆发的情况下的GDP降低了约11％。
The COVID-19 pandemic has caused more than 8 million confirmed cases and 500,000 death to date. In response to this emergency, many countries have introduced a series of social-distancing measures including lockdowns and businesses' temporary shutdowns, in an attempt to curb the spread of the infection. Accordingly, the pandemic has been generating unprecedent disruption on practically every aspect of society. This paper demonstrates that high-frequency electricity market data can be used to estimate the causal, short-run impact of COVID-19 on the economy. In the current uncertain economic conditions, timeliness is essential. Unlike official statistics, which are published with a delay of a few months, with our approach one can monitor virtually every day the impact of the containment policies, the extent of the recession and measure whether the monetary and fiscal stimuli introduced to address the crisis are being effective. We illustrate our methodology on daily data for the Italian day-ahead power market. Not surprisingly, we find that the containment measures caused a significant reduction in economic activities and that the GDP at the end of in May 2020 is still about 11% lower that what it would have been without the outbreak.
